TO USE IF YOU DON’T WANT TO USE AUTOMATIC GATING FOR nonDEBRIS AND SINGLETS
#source("http://www.bioconductor.org/biocLite.R")
#biocLite("BiocUpgrade")
library(tidyverse)
## ── Attaching packages ─────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
## ✔ ggplot2 3.2.1 ✔ purrr 0.3.2
## ✔ tibble 2.1.3 ✔ dplyr 0.8.3
## ✔ tidyr 0.8.3 ✔ stringr 1.4.0
## ✔ readr 1.3.1 ✔ forcats 0.4.0
## ── Conflicts ────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
library(openCyto)
## Loading required package: flowWorkspace
## Loading required package: flowCore
##
## Attaching package: 'flowCore'
## The following object is masked from 'package:tibble':
##
## view
## Loading required package: ncdfFlow
## Loading required package: RcppArmadillo
## Loading required package: BH
## Registered S3 method overwritten by 'R.oo':
## method from
## throw.default R.methodsS3
library(flowViz)
## Loading required package: lattice
##
## Attaching package: 'lattice'
## The following objects are masked from 'package:ncdfFlow':
##
## densityplot, histogram, xyplot
library(flowUtils)
library(flowDensity)
## Warning: replacing previous import 'flowCore::plot' by 'graphics::plot'
## when loading 'flowDensity'
library(ggplot2)
library(dplyr)
library(ggcyto)
library(flowWorkspace)
#Load fcs file
fcsFile <- list.files(path = "FCS/", pattern = ".fcs")
fs <- read.flowSet(fcsFile, path = "FCS/")
fcsFile <- read.FCS("FCS/WT.fcs")
#Explore data
fcsFile
## flowFrame object 'WT.fcs'
## with 50000 cells and 34 observables:
## name desc range minRange
## $P1 Time <NA> 262144 0.00000
## $P2 FSC-A FSC-A 262144 0.00000
## $P3 FSC-H FSC-H 262144 0.00000
## $P4 FSC-W FSC-W 262144 0.00000
## $P5 YellowGreen_D-A YellowGreen_D-A 262144 -38.06389
## $P6 YellowGreen_D-H YellowGreen_D-H 262144 0.00000
## $P7 YellowGreen_D-W YellowGreen_D-W 262144 0.00000
## $P8 PE-CF594 (YG)-A CD142 (F3) PE-CF594 (YG)-A 262144 -111.00000
## $P9 PE-CF594 (YG)-H CD142 (F3) PE-CF594 (YG)-H 262144 0.00000
## $P10 PE-CF594 (YG)-W CD142 (F3) PE-CF594 (YG)-W 262144 0.00000
## $P11 YellowGreen_B-A YellowGreen_B-A 262144 -111.00000
## $P12 YellowGreen_B-H YellowGreen_B-H 262144 0.00000
## $P13 YellowGreen_B-W YellowGreen_B-W 262144 0.00000
## $P14 YellowGreen_A-A YellowGreen_A-A 262144 -42.73840
## $P15 YellowGreen_A-H YellowGreen_A-H 262144 0.00000
## $P16 YellowGreen_A-W YellowGreen_A-W 262144 0.00000
## $P17 SB436*-A SCA1 SB436*-A 262144 -106.91323
## $P18 SB436*-H SCA1 SB436*-H 262144 0.00000
## $P19 SB436*-W SCA1 SB436*-W 262144 0.00000
## $P20 Violet_A-A Violet_A-A 262144 -111.00000
## $P21 Violet_A-H Violet_A-H 262144 0.00000
## $P22 Violet_A-W Violet_A-W 262144 0.00000
## $P23 SSC-A SSC-A 262144 0.00000
## $P24 SSC-H SSC-H 262144 0.00000
## $P25 SSC-W SSC-W 262144 0.00000
## $P26 FITC-A LIN Sytox FITC-A 262144 -111.00000
## $P27 FITC-H LIN Sytox FITC-H 262144 0.00000
## $P28 FITC-W LIN Sytox FITC-W 262144 0.00000
## $P29 Blue_A-A Blue_A-A 262144 -111.00000
## $P30 Blue_A-H Blue_A-H 262144 0.00000
## $P31 Blue_A-W Blue_A-W 262144 0.00000
## $P32 IndexSort <NA> 262144 0.00000
## $P33 DeltaTime <NA> 262144 0.00000
## $P34 RegionClassification <NA> 262144 0.00000
## maxRange
## $P1 262143
## $P2 262143
## $P3 262143
## $P4 262143
## $P5 262143
## $P6 262143
## $P7 262143
## $P8 262143
## $P9 262143
## $P10 262143
## $P11 262143
## $P12 262143
## $P13 262143
## $P14 262143
## $P15 262143
## $P16 262143
## $P17 262143
## $P18 262143
## $P19 262143
## $P20 262143
## $P21 262143
## $P22 262143
## $P23 262143
## $P24 262143
## $P25 262143
## $P26 262143
## $P27 262143
## $P28 262143
## $P29 262143
## $P30 262143
## $P31 262143
## $P32 262143
## $P33 262143
## $P34 262143
## 650 keywords are stored in the 'description' slot
exprs(fcsFile)[1:10,]
## Time FSC-A FSC-H FSC-W YellowGreen_D-A YellowGreen_D-H
## [1,] 65560 73248.23 66388 72308.18 52.08743 68
## [2,] 65563 81118.24 73605 72225.61 83.47344 101
## [3,] 65566 93843.24 81072 75859.87 206.34636 144
## [4,] 65567 156827.69 106980 96072.72 1891.17432 1152
## [5,] 65571 91272.77 79860 74901.74 286.48087 292
## [6,] 65572 22784.01 29657 50348.08 54.75858 121
## [7,] 65573 45077.27 51700 57140.89 40.73504 68
## [8,] 65574 38232.46 48609 51546.06 16.69469 37
## [9,] 65575 174569.39 128721 88878.89 96.16141 97
## [10,] 65575 60061.82 63078 62402.29 182.30600 198
## YellowGreen_D-W PE-CF594 (YG)-A PE-CF594 (YG)-H PE-CF594 (YG)-W
## [1,] 50200.03 124.20848 288 28264.33
## [2,] 54163.52 453.42773 529 56173.61
## [3,] 93910.52 1065.12109 884 78963.55
## [4,] 107586.80 9799.78223 6128 104803.94
## [5,] 64297.30 1405.02502 976 94343.98
## [6,] 29658.33 347.91733 509 44795.89
## [7,] 39258.99 267.11502 464 37727.70
## [8,] 29570.35 70.78548 181 25629.82
## [9,] 64969.42 538.90454 549 64330.88
## [10,] 60341.45 1123.21863 1170 62915.60
## YellowGreen_B-A YellowGreen_B-H YellowGreen_B-W YellowGreen_A-A
## [1,] -14.691326 38 0.000 30.050440
## [2,] 56.761940 64 58124.227 94.825836
## [3,] 79.466721 120 43399.426 30.050440
## [4,] 473.461365 306 101401.195 212.356445
## [5,] 114.191673 148 50565.305 61.436455
## [6,] 22.704777 59 25220.004 18.030264
## [7,] 11.352388 31 23999.682 12.020176
## [8,] 6.677876 45 9725.361 4.674513
## [9,] 38.731678 58 43764.125 12.020176
## [10,] 72.121056 124 38117.141 8.013451
## YellowGreen_A-H YellowGreen_A-W SB436*-A SB436*-H SB436*-W
## [1,] 66 29839.178 47.07373 50 61700.48
## [2,] 112 55486.660 145.21051 132 72094.82
## [3,] 76 25912.971 5415.87305 2940 120726.06
## [4,] 210 66271.391 18330.83203 8150 147402.38
## [5,] 64 62910.930 182.70992 160 74837.98
## [6,] 47 25141.094 2530.81152 2591 64013.61
## [7,] 47 16760.730 3493.03076 2459 93094.45
## [8,] 45 6807.753 11.96790 41 19129.96
## [9,] 46 17125.092 160.36984 126 83412.69
## [10,] 40 13129.237 1377.10620 1080 83564.84
## Violet_A-A Violet_A-H Violet_A-W SSC-A SSC-H SSC-W
## [1,] 230.5815 182 83029.62 17580.359 15158 76009.13
## [2,] 1443.3286 1012 93468.36 236985.156 210447 73800.34
## [3,] 5213.2168 2808 121671.43 42554.961 34266 81389.19
## [4,] 15389.9199 6886 146470.20 84185.953 57786 95476.59
## [5,] 2344.1123 1780 86305.48 119029.742 110182 70798.61
## [6,] 2245.1777 2363 62268.29 14038.583 17942 51278.15
## [7,] 3035.8569 2235 89019.21 19821.965 20998 61865.53
## [8,] 411.6957 537 50243.74 8782.381 11199 51394.06
## [9,] 1876.5665 1418 86729.66 62098.676 55731 73023.98
## [10,] 1568.5925 1388 74062.89 26110.691 25612 66812.05
## FITC-A FITC-H FITC-W Blue_A-A Blue_A-H Blue_A-W
## [1,] 50.53441 64 51747.23 64.88368 176 24160.32
## [2,] 522.81274 473 72437.75 429.85440 553 50942.02
## [3,] 10396.98633 5804 117397.81 709.35333 524 88717.91
## [4,] 786.71466 552 93402.41 569.60388 540 69128.81
## [5,] 535.91425 528 66518.33 521.56500 544 62833.24
## [6,] 114.79421 148 50832.12 20.58809 64 21082.21
## [7,] 2468.07544 2208 73255.34 187.16447 288 42590.32
## [8,] 4163.78564 4701 58046.77 235.20335 457 33729.29
## [9,] 588.94421 421 91679.45 358.73190 709 33159.17
## [10,] 121.03303 138 57478.41 227.71678 282 52920.73
## IndexSort DeltaTime RegionClassification
## [1,] 3.433181e-43 14860 3.433181e-43
## [2,] 3.447194e-43 34917 3.447194e-43
## [3,] 3.461207e-43 22024 3.461207e-43
## [4,] 3.475220e-43 16769 3.475220e-43
## [5,] 3.489233e-43 39784 3.489233e-43
## [6,] 3.503246e-43 10731 3.503246e-43
## [7,] 3.517259e-43 11606 3.517259e-43
## [8,] 3.531272e-43 4878 3.531272e-43
## [9,] 3.545285e-43 9499 3.545285e-43
## [10,] 3.559298e-43 4788 3.559298e-43
summary(fcsFile)
## Time FSC-A FSC-H FSC-W YellowGreen_D-A
## Min. 65560.00 10491.68 16385.00 41275.07 -38.06389
## 1st Qu. 91217.75 40716.46 47699.75 54529.40 34.72495
## Median 105479.00 64927.12 64394.00 63797.59 93.49026
## Mean 105433.80 80032.53 65176.82 75278.46 399.52412
## 3rd Qu. 130450.00 100935.00 83249.75 80094.26 219.03432
## Max. 134614.00 262143.00 157182.00 262143.00 40034.53125
## YellowGreen_D-H YellowGreen_D-W PE-CF594 (YG)-A PE-CF594 (YG)-H
## Min. 0.0000 0.00 -303.1755 0.000
## 1st Qu. 61.0000 36300.48 189.6517 308.000
## Median 109.0000 53865.33 545.5825 592.000
## Mean 326.0931 56931.04 2103.5276 1691.087
## 3rd Qu. 199.0000 70335.20 1236.9095 1097.000
## Max. 18252.0000 262143.00 202922.6094 93018.000
## PE-CF594 (YG)-W YellowGreen_B-A YellowGreen_B-H YellowGreen_B-W
## Min. 0.00 -298.50104 0.0000 0.00
## 1st Qu. 39793.74 20.03363 51.0000 26258.48
## Median 56681.50 58.09752 79.0000 47265.26
## Mean 59809.87 144.25967 130.0085 50372.73
## 3rd Qu. 72547.70 123.54070 124.0000 66074.11
## Max. 262143.00 30012.37500 3866.0000 262143.00
## YellowGreen_A-A YellowGreen_A-H YellowGreen_A-W SB436*-A
## Min. -42.73840 0.0000 0.00 -106.91323
## 1st Qu. 14.69133 56.0000 15977.38 50.26517
## Median 43.40619 88.0000 31764.29 161.96556
## Mean 93.89599 117.6865 35545.20 2552.95226
## 3rd Qu. 94.15804 136.0000 48243.92 1572.78137
## Max. 33482.86719 3474.0000 262143.00 262143.00000
## SB436*-H SB436*-W Violet_A-A Violet_A-H Violet_A-W
## Min. 0.000 0.00 -374.9942 1.000 0.00
## 1st Qu. 57.000 55487.38 828.9764 718.000 63868.26
## Median 121.000 77066.57 1794.3870 1394.000 78687.79
## Mean 1491.243 82917.51 4221.4875 2619.989 90851.86
## 3rd Qu. 1099.250 102165.34 4329.1880 2941.000 102654.50
## Max. 258896.000 262143.00 262143.0000 258256.000 262143.00
## SSC-A SSC-H SSC-W FITC-A FITC-H FITC-W
## Min. 18.09257 6.00 38656.43 -1033.7717 0.00 0.00
## 1st Qu. 18163.06445 20342.00 55613.73 378.6961 346.00 54595.46
## Median 44083.78320 42840.00 64319.55 2775.3372 2502.50 61923.80
## Mean 73505.91199 66893.04 67827.44 25105.1255 25834.88 68732.60
## 3rd Qu. 87668.61719 74835.50 72495.57 23922.2710 23355.50 73858.70
## Max. 262143.00000 257711.00 262143.00 262143.0000 258685.00 262143.00
## Blue_A-A Blue_A-H Blue_A-W IndexSort DeltaTime
## Min. -113.5464 0.000 0.00 3.138909e-43 34.000
## 1st Qu. 297.5915 404.000 43712.00 3.236999e-43 1318.000
## Median 586.4487 670.000 52687.47 3.349103e-43 3693.000
## Mean 4623.6101 4641.691 56405.74 3.355948e-43 6137.882
## 3rd Qu. 2738.2163 2515.250 63267.57 3.461207e-43 8164.250
## Max. 262143.0000 258047.000 262143.00 3.573311e-43 262144.000
## RegionClassification
## Min. 0.000000e+00
## 1st Qu. 3.265025e-43
## Median 3.405155e-43
## Mean 5.732300e+00
## 3rd Qu. 3.545285e-43
## Max. 6.200000e+01
str(keyword(fcsFile))
## List of 650
## $ FCSversion : chr "3.1"
## $ $PAR : chr "34"
## $ $DATATYPE : chr "F"
## $ $MODE : chr "L"
## $ $BYTEORD : chr "1,2,3,4"
## $ $TOT : chr "50000"
## $ $BEGINDATA : chr " 12411"
## $ $ENDDATA : chr " 6812410"
## $ $BEGINSTEXT : chr "0"
## $ $ENDSTEXT : chr "0"
## $ $BEGINANALYSIS : chr "0"
## $ $ENDANALYSIS : chr "0"
## $ $NEXTDATA : chr "0"
## $ $TIMESTEP : chr "0.01"
## $ $DATE : chr "16-JUL-2018"
## $ $BTIM : chr "14:23:38.72"
## $ $ETIM : chr "14:24:48.23"
## $ EXPORT TIME : chr "16-JUL-2018 16:32:39.32"
## $ $P1N : chr "Time"
## $ $P1B : chr "32"
## $ $P1E : chr "0,0"
## $ $P1R : chr "262144"
## $ P1KIND : chr "Time"
## $ $P2N : chr "FSC-A"
## $ $P2B : chr "32"
## $ $P2E : chr "0,0"
## $ $P2R : chr "262144"
## $ $P2V : chr "95"
## $ $P2S : chr "FSC-A"
## $ P2MEAS : chr "A"
## $ P2THRESHOLD : chr "16358"
## $ P2MS : chr "1000"
## $ P2KIND : chr "SCATTER"
## $ P2TARGETVALUE : chr "0.0790596211908806"
## $ P2FLUOR : chr "FSC"
## $ P2DET : chr "FSC"
## $ $P2L : chr "488"
## $ FL2ABD : chr "99945"
## $ FL2SLOPE : chr "0.00386796775273979"
## $ FL2INTERCEPT : chr "3.53559565544128"
## $ $P3N : chr "FSC-H"
## $ $P3B : chr "32"
## $ $P3E : chr "0,0"
## $ $P3R : chr "262144"
## $ $P3V : chr "95"
## $ $P3S : chr "FSC-H"
## $ P3MEAS : chr "H"
## $ P3THRESHOLD : chr "16358"
## $ P3MS : chr "1000"
## $ P3KIND : chr "SCATTER"
## $ P3TARGETVALUE : chr "0.0790596211908806"
## $ P3FLUOR : chr "FSC"
## $ P3DET : chr "FSC"
## $ $P3L : chr "488"
## $ FL3ABD : chr "99945"
## $ FL3SLOPE : chr "0.00386796775273979"
## $ FL3INTERCEPT : chr "3.53559565544128"
## $ $P4N : chr "FSC-W"
## $ $P4B : chr "32"
## $ $P4E : chr "0,0"
## $ $P4R : chr "262144"
## $ $P4V : chr "95"
## $ $P4S : chr "FSC-W"
## $ P4MEAS : chr "W"
## $ P4THRESHOLD : chr "16358"
## $ P4KIND : chr "SCATTER"
## $ P4TARGETVALUE : chr "0.0790596211908806"
## $ P4FLUOR : chr "FSC"
## $ P4DET : chr "FSC"
## $ $P4L : chr "488"
## $ FL4ABD : chr "99945"
## $ FL4SLOPE : chr "0.00386796775273979"
## $ FL4INTERCEPT : chr "3.53559565544128"
## $ $P5N : chr "YellowGreen_D-A"
## $ $P5B : chr "32"
## $ $P5E : chr "0,0"
## $ $P5R : chr "262144"
## $ $P5V : chr "450"
## $ $P5S : chr "YellowGreen_D-A"
## $ P5MEAS : chr "A"
## $ P5MS : chr "1000"
## $ P5KIND : chr "COLOR"
## $ P5TARGETVALUE : chr "1.19"
## $ $P5F : chr "BP/582/15/BP/582/15"
## $ P5FLUOR : chr "YellowGreen_D"
## $ P5DET : chr "PE (YG)"
## $ $P5L : chr "561"
## $ FL5ABD : chr "15018"
## $ FL5SLOPE : chr "8.72256278991699"
## $ FL5INTERCEPT : chr "-18.934476852417"
## $ $P6N : chr "YellowGreen_D-H"
## $ $P6B : chr "32"
## $ $P6E : chr "0,0"
## $ $P6R : chr "262144"
## $ $P6V : chr "450"
## $ $P6S : chr "YellowGreen_D-H"
## $ P6MEAS : chr "H"
## $ P6MS : chr "1000"
## $ P6KIND : chr "COLOR"
## [list output truncated]
summary(fcsFile[,c(2, 8, 17, 23, 26)])
## FSC-A PE-CF594 (YG)-A SB436*-A SSC-A FITC-A
## Min. 10491.68 -303.1755 -106.91323 18.09257 -1033.7717
## 1st Qu. 40716.46 189.6517 50.26517 18163.06445 378.6961
## Median 64927.12 545.5825 161.96556 44083.78320 2775.3372
## Mean 80032.53 2103.5276 2552.95226 73505.91199 25105.1255
## 3rd Qu. 100935.00 1236.9095 1572.78137 87668.61719 23922.2710
## Max. 262143.00 202922.6094 262143.00000 262143.00000 262143.0000
#Compensation Check $SPILLOVER for correct file by changing the x in spillover(fcsFile)[[x]] in the console
#Single file
fcsFile_comp <- compensate(fcsFile, spillover(fcsFile)[[3]])
fcsFile_comp
## flowFrame object 'WT.fcs'
## with 50000 cells and 34 observables:
## name desc range minRange
## $P1 Time <NA> 262144 0.00000
## $P2 FSC-A FSC-A 262144 0.00000
## $P3 FSC-H FSC-H 262144 0.00000
## $P4 FSC-W FSC-W 262144 0.00000
## $P5 YellowGreen_D-A YellowGreen_D-A 262144 -38.06389
## $P6 YellowGreen_D-H YellowGreen_D-H 262144 0.00000
## $P7 YellowGreen_D-W YellowGreen_D-W 262144 0.00000
## $P8 PE-CF594 (YG)-A CD142 (F3) PE-CF594 (YG)-A 262144 -111.00000
## $P9 PE-CF594 (YG)-H CD142 (F3) PE-CF594 (YG)-H 262144 0.00000
## $P10 PE-CF594 (YG)-W CD142 (F3) PE-CF594 (YG)-W 262144 0.00000
## $P11 YellowGreen_B-A YellowGreen_B-A 262144 -111.00000
## $P12 YellowGreen_B-H YellowGreen_B-H 262144 0.00000
## $P13 YellowGreen_B-W YellowGreen_B-W 262144 0.00000
## $P14 YellowGreen_A-A YellowGreen_A-A 262144 -42.73840
## $P15 YellowGreen_A-H YellowGreen_A-H 262144 0.00000
## $P16 YellowGreen_A-W YellowGreen_A-W 262144 0.00000
## $P17 SB436*-A SCA1 SB436*-A 262144 -106.91323
## $P18 SB436*-H SCA1 SB436*-H 262144 0.00000
## $P19 SB436*-W SCA1 SB436*-W 262144 0.00000
## $P20 Violet_A-A Violet_A-A 262144 -111.00000
## $P21 Violet_A-H Violet_A-H 262144 0.00000
## $P22 Violet_A-W Violet_A-W 262144 0.00000
## $P23 SSC-A SSC-A 262144 0.00000
## $P24 SSC-H SSC-H 262144 0.00000
## $P25 SSC-W SSC-W 262144 0.00000
## $P26 FITC-A LIN Sytox FITC-A 262144 -111.00000
## $P27 FITC-H LIN Sytox FITC-H 262144 0.00000
## $P28 FITC-W LIN Sytox FITC-W 262144 0.00000
## $P29 Blue_A-A Blue_A-A 262144 -111.00000
## $P30 Blue_A-H Blue_A-H 262144 0.00000
## $P31 Blue_A-W Blue_A-W 262144 0.00000
## $P32 IndexSort <NA> 262144 0.00000
## $P33 DeltaTime <NA> 262144 0.00000
## $P34 RegionClassification <NA> 262144 0.00000
## maxRange
## $P1 262143
## $P2 262143
## $P3 262143
## $P4 262143
## $P5 262143
## $P6 262143
## $P7 262143
## $P8 262143
## $P9 262143
## $P10 262143
## $P11 262143
## $P12 262143
## $P13 262143
## $P14 262143
## $P15 262143
## $P16 262143
## $P17 262143
## $P18 262143
## $P19 262143
## $P20 262143
## $P21 262143
## $P22 262143
## $P23 262143
## $P24 262143
## $P25 262143
## $P26 262143
## $P27 262143
## $P28 262143
## $P29 262143
## $P30 262143
## $P31 262143
## $P32 262143
## $P33 262143
## $P34 262143
## 650 keywords are stored in the 'description' slot
#All files
comp <- fsApply(fs, function(x)spillover(x)[[3]], simplify = FALSE)
fs_comp <- compensate(fs, comp)
#Autoplot
for (i in 1:length(fs_comp)){
print(autoplot(fs_comp[i], x = "FSC-A", y = "SSC-A", bins = 256))
}
#Transform
tf <- estimateLogicle(fs_comp[[1]], channels = colnames(fs_comp[,c(5:16, 20:22, 26:31)]))
fs_trans <- transform(fs, tf)
##Manual gating #Gating nonDebris
gs <- GatingSet(fs_trans)
## ......done!
rg1 <- rectangleGate("FSC-H" = c(25000, Inf), filterId = "nonDebris")
add(gs, rg1, parent = "root")
## replicating filter 'nonDebris' across samples!
## [1] 2
getNodes(gs)
## [1] "root" "/nonDebris"
recompute(gs)
## ......done!
for(i in 1:length(gs)){
print(autoplot(gs[i], x = "FSC-H", y = "SSC-H", "nonDebris", bins = 256))
}
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
#Gate the singlets
rg2 <- rectangleGate("FSC-H" = c(25000, 115000), "FSC-W" = c(40000, 100000))
add(gs, rg2, parent = "nonDebris", name = "singlets")
## replicating filter 'defaultRectangleGate' across samples!
## [1] 3
getNodes(gs)
## [1] "root" "/nonDebris" "/nonDebris/singlets"
recompute(gs)
## .
## .....done!
for(i in 1:length(gs)){
print(autoplot(gs[i], x = "FSC-H", y = "FSC-W", "singlets", bins = 256))
}
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
#Check gating percentages
plot(gs)
getStats(gs)
getStats(gs, "singlets", "percent")
fs_singlets <- getData(gs, "/nonDebris/singlets")
fsApply(fs_singlets, each_col, median)
## Time FSC-A FSC-H FSC-W YellowGreen_D-A
## FITC-Control.fcs 54990.0 61796.60 63819.5 63404.76 0.8171976
## PE-Control.fcs 38658.0 62835.21 64400.0 63263.06 0.7509889
## SB436*-Control.fcs 24210.0 64032.73 65222.0 63668.99 0.6455054
## SGCB.fcs 62156.0 65375.72 67381.0 63041.43 1.2213547
## Unstained.fcs 195165.5 65210.27 66417.5 63380.37 0.6599985
## WT.fcs 105565.0 58540.27 62005.5 61305.29 0.9764306
## YellowGreen_D-H YellowGreen_D-W PE-CF594 (YG)-A
## FITC-Control.fcs 0.9729007 3.742497 1.595052
## PE-Control.fcs 0.9325262 3.714147 1.546371
## SB436*-Control.fcs 0.8745986 3.660079 1.481288
## SGCB.fcs 1.2785671 3.831724 1.985405
## Unstained.fcs 0.8814170 3.667445 1.520421
## WT.fcs 1.0886796 3.783278 1.717615
## PE-CF594 (YG)-H PE-CF594 (YG)-W YellowGreen_B-A
## FITC-Control.fcs 1.732888 3.791437 0.7564152
## PE-Control.fcs 1.700727 3.775393 0.7340776
## SB436*-Control.fcs 1.663729 3.755418 0.7225544
## SGCB.fcs 2.046228 3.847393 0.9535631
## Unstained.fcs 1.691236 3.763842 0.7725772
## WT.fcs 1.821133 3.809321 0.7509171
## YellowGreen_B-H YellowGreen_B-W YellowGreen_A-A
## FITC-Control.fcs 0.9560436 3.727601 0.6890139
## PE-Control.fcs 0.9385229 3.714307 0.6625586
## SB436*-Control.fcs 0.9385229 3.707603 0.6625586
## SGCB.fcs 1.0801104 3.797971 0.8242880
## Unstained.fcs 0.9617340 3.727690 0.7080227
## WT.fcs 0.9502796 3.718171 0.6418299
## YellowGreen_A-H YellowGreen_A-W SB436*-A SB436*-H
## FITC-Control.fcs 1.0248713 3.564456 47.87159 58
## PE-Control.fcs 0.9996475 3.558388 51.06303 59
## SB436*-Control.fcs 1.0149536 3.546489 118.08327 102
## SGCB.fcs 1.0970851 3.648044 264.88950 227
## Unstained.fcs 1.0440630 3.567010 60.63735 63
## WT.fcs 0.9996475 3.537715 127.65759 111
## SB436*-W Violet_A-A Violet_A-H Violet_A-W SSC-A
## FITC-Control.fcs 55193.47 2.212702 2.106794 3.938275 48311.52
## PE-Control.fcs 56091.35 1.887094 1.817161 3.947655 46746.82
## SB436*-Control.fcs 73464.92 2.077191 1.975272 3.981699 47052.53
## SGCB.fcs 74133.54 2.346445 2.291792 3.956798 44044.17
## Unstained.fcs 62223.37 1.942009 1.847218 3.974563 45778.87
## WT.fcs 72358.90 2.276874 2.215336 3.954405 37525.85
## SSC-H SSC-W FITC-A FITC-H FITC-W Blue_A-A
## FITC-Control.fcs 46978.0 64158.11 2.541522 2.568674 3.878926 1.918755
## PE-Control.fcs 45496.0 63439.20 1.330842 1.416554 3.829795 1.385001
## SB436*-Control.fcs 45600.5 64375.83 1.448883 1.493529 3.843753 1.454761
## SGCB.fcs 43455.0 63822.00 2.930536 2.909542 3.888762 1.974278
## Unstained.fcs 44671.0 64153.86 1.321736 1.389680 3.846187 1.450278
## WT.fcs 37614.0 61997.80 2.673365 2.681019 3.860606 1.763519
## Blue_A-H Blue_A-W IndexSort DeltaTime
## FITC-Control.fcs 1.997960 3.804356 3.349103e-43 48559.5
## PE-Control.fcs 1.610639 3.708254 3.349103e-43 48764.0
## SB436*-Control.fcs 1.661452 3.730474 3.349103e-43 21263.5
## SGCB.fcs 2.058303 3.809151 3.349103e-43 3538.0
## Unstained.fcs 1.651052 3.729638 3.349103e-43 10045.0
## WT.fcs 1.890420 3.788804 3.349103e-43 3785.5
## RegionClassification
## FITC-Control.fcs 3.349103e-43
## PE-Control.fcs 3.349103e-43
## SB436*-Control.fcs 3.349103e-43
## SGCB.fcs 3.405155e-43
## Unstained.fcs 3.349103e-43
## WT.fcs 3.405155e-43
#Gate FITC
LinGate <- polygonGate("FSC-A" = c(40000, 40000, 100000, 200000, 200000), "FITC-A" = c(0, 1.5, 2.2, 2.2,0))
add(gs, LinGate, parent = "singlets", name = "Lineage negative")
## replicating filter 'defaultPolygonGate' across samples!
## [1] 4
getNodes(gs)
## [1] "root"
## [2] "/nonDebris"
## [3] "/nonDebris/singlets"
## [4] "/nonDebris/singlets/Lineage negative"
recompute(gs)
## .
## .....done!
for(i in 1:length(gs)){
print(autoplot(gs[i], x = 'FSC-A', y = 'FITC-A', "Lineage negative", log = "FITC-A", bins = 256))
}
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
#gate PE and SB436
F3 <- quadGate("PE-CF594 (YG)-A" = 2.4, "Violet_A-A" = 2.6)
add(gs, F3, parent = "Lineage negative", name = c("Sca1+F3-", "Sca1+F3+", "Sca1- F3+", "Sca1-F3-"))
## replicating filter 'defaultQuadGate' across samples!
## [1] 5 6 7 8
getNodes(gs)
## [1] "root"
## [2] "/nonDebris"
## [3] "/nonDebris/singlets"
## [4] "/nonDebris/singlets/Lineage negative"
## [5] "/nonDebris/singlets/Lineage negative/Sca1+F3-"
## [6] "/nonDebris/singlets/Lineage negative/Sca1+F3+"
## [7] "/nonDebris/singlets/Lineage negative/Sca1- F3+"
## [8] "/nonDebris/singlets/Lineage negative/Sca1-F3-"
recompute(gs)
## .
## .....done!
getStats(gs, c("Sca1+F3-", "Sca1+F3+", "Sca1- F3+", "Sca1-F3-"), "percent")
for(i in 1:length(gs)){
print(autoplot(gs[i], x = "PE-CF594 (YG)-A", y = "Violet_A-A" , c("Sca1+F3-", "Sca1+F3+", "Sca1- F3+", "Sca1-F3-"), bins = 256))
}
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.